Ling Shao 

 

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Journal Articles

F. Zheng, Y. Tang and L. Shao, “Hetero-manifold Regularisation for Cross-modal Hashing”, Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), doi: 10.1109/TPAMI.2016.2645565.

M. Yu, L. Liu and L. Shao, “Structure-Preserving Binary Representations for RGB-D Action Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), vol. 38, no. 8, pp. 1651-1664, Aug. 2016.

M. Yu, L. Shao, X. Zhen and X. He, “Local Feature Discriminant Projection”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), vol. 38, no. 9, pp. 1908-1914, Sep. 2016.

L. Liu, M. Yu and L. Shao, “Latent Structure Preserving Hashing”, International Journal of Computer Vision (IJCV), vol. 122, no. 3, pp. 439-457, May 2017.

D. Wu, L. Pigou, P.-J. Kindermans, N. Le, L. Shao, J. Dambre and J.-M. Odobez, “Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), vol. 38, no. 8, pp. 1583-1597, Aug. 2016.

L. Shao, L. Liu and M. Yu, Kernelized Multiview Projection for Robust Action Recognition, International Journal of Computer Vision (IJCV), vol. 118, no. 2, pp. 115-129, Jun. 2016.

M. Yu, L. Liu and L. Shao, “Binary Set Embedding for Cross-modal Retrieval”, Accepted by IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2016.2609463.

L. Liu, M. Yu and L. Shao, “Learning Short Binary Codes for Large-scale Image Retrieval”, IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1289-1299, Mar. 2017.

J. Xie, F. Zhu, G. Dai, L. Shao and Y. Fang, “Progressive Shape-Distribution-Encoder for Learning 3D Shape Representation”, IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1231-1242, Mar. 2017.

Y. Guo, G. Ding, L. Liu, J. Han and L. Shao, “Learning to Hash with Optimized Anchor Embedding for Scalable Retrieval”, IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1344-1354, Mar. 2017. 

Z. Zhang, Z. Lai, Y. Xu, L. Shao and G. S. Xie, “Discriminative Elastic-Net Regularized Linear Regression”, IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1466-1481, Mar. 2017.

Y. Tang and L. Shao, “Pairwise Operator Learning for Patch Based Single-image Super-resolution”, IEEE Transactions on Image Processing, vol. 26, no. 2, pp. 994-1003, Feb. 2017.

L. Zhang, H. Shum and L. Shao, “Manifold Regularized Experimental Design for Active Learning”, IEEE Transactions on Image Processing, vol. 26, no. 2, pp. 969-981, Feb. 2017.

L. Liu, Z. Lin, L. Shao, F. Shen, G. Ding and J. Han, “Sequential Discrete Hashing for Scalable Cross-Modality Similarity Retrieval”, IEEE Transactions on Image Processing, vol. 26, no. 1, pp. 107-118, Jan. 2017.

X. Dong, J. Shen and L. Shao, “HSP2P: Hierarchical Superpixel-to-Pixel Dense Image Matching”, Accepted by IEEE Transactions on Circuits and Systems for Video Technology, doi: 10.1109/TCSVT.2016.2595321, 2016.

B. Ma, L. Huang, J. Shen, L. Shao, M.-H. Yang and F. Porikli, “Visual Tracking under Motion Blur”, IEEE Transactions on Image Processing, vol. 25, no. 12, pp. 5867-5876, Dec. 2016.

 

J. Shen, X. Hao, Z. Liang, Y. Liu, W. Wang and L. Shao, “Real-Time Superpixel Segmentation by DBSCAN Clustering Algorithm”, IEEE Transactions on Image Processing, vol. 25, no. 12, pp. 5933-5942, Dec. 2016.

W. Wang, J. Shen, L. Shao and F. Porikli, “Correspondence Driven Saliency Transfer”, IEEE Transactions on Image Processing, vol. 25, no. 11, pp. 5025-5034, Nov. 2016.

B. Ma, H. Hu, J. Shen, Y. Liu and L. Shao, “Generalized Pooling for Robust Object Tracking”, IEEE Transactions on Image Processing, vol. 25, no. 9, pp. 4199-4208, Sep. 2016.

J. Tang, K. Wang and L. Shao, “Supervised Matrix Factorization Hashing for Cross-Modal Retrieval”, IEEE Transactions on Image Processing, vol. 25, no. 7, pp. 3157 – 3166, Jul. 2016. [Code]

R. Yan and L. Shao, “Blind Image Blur Estimation via Deep Learning”, IEEE Transactions on Image Processing, vol. 25, no. 4, pp. 1910-1921, Feb. 2016.

L. Zhang, H. Shum and L. Shao, “Discriminative Semantic Subspace Analysis for Relevance Feedback”, IEEE Transactions on Image Processing, vol. 25, no. 3, pp. 1275-1287, Mar. 2016.

J. Qin, L. Liu, Z. Zhang, Y. Wang and L. Shao, “Compressive Sequential Learning for Action Similarity Labeling”, IEEE Transactions on Image Processing, vol. 25, no. 2, pp. 756-769, Feb. 2016.

X. Dong, J. Shen, L. Shao and L. V. Gool, “Sub-Markov Random Walk for Image Segmentation”, IEEE Transactions on Image Processing, vol. 25, no. 2, pp. 516-527, Feb. 2016.

F. Zhu, L. Shao and Y. Fang, “Boosted Cross-Domain Dictionary Learning for Visual Categorization”, IEEE Intelligent Systems, vol. 31, no. 3, pp. 6-18, May 2016.

L. Liu and L. Shao, “Sequential Compact Code Learning for Unsupervised Image Hashing”, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 12, pp. 2526-2536, Dec. 2016.

W. Zhang, J. Han, J. Han and L. Shao, Cosaliency Detection Based on Intrasaliency Prior Transfer and Deep Intersaliency Mining”, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 6, pp. 1163 – 1176, Jun. 2016.

S. Tan, F. Zheng, L. Liu, J. Han and L. Shao, “Dense Invariant Feature Based Support Vector Ranking for Cross-Camera Person Re-identification”, Accepted by IEEE Transactions on Circuits and Systems for Video Technology, doi: 10.1109/TCSVT.2016.2555739.

L. Liu, M. Yu and L. Shao, “Unsupervised Local Feature Hashing for Image Similarity Search”, IEEE Transactions on Cybernetics, vol. 46, no. 11, pp. 2548-2558, Nov. 2016.

B. Ma, L. Huang, J. Shen and L. Shao, “Discriminative Visual Tracking Using Tensor Pooling”, IEEE Transactions on Cybernetics, vol. 46, no. 11, pp. 2411-2422, Nov. 2016.

J. Tang, L. Shao, X. Li and K. Lu, “A Local Structural Descriptor for Image Matching via Normalized Graph Laplacian Embedding”, IEEE Transactions on Cybernetics, vol. 46, no. 2, pp. 410-420, Feb. 2016.

L. Liu, L. Shao, X. Li and K. Lu, “Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach, IEEE Transactions on Cybernetics, vol. 45, no. 1, pp. 158-170, Jan. 2016.

W. Wang, J. Shen and L. Shao, “Consistent Video Saliency Using Local Gradient Flow Optimization and Global Refinement”, IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 4185-4196, Nov. 2015.

X. Dong, J. Shen, L. Shao and M.-H. Yang, “Interactive Cosegmentation Using Global and Local Energy Optimization”, IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 3966 – 3977, Nov. 2015.

Q. Zhu, J. Mai and L. Shao, “A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior”, IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 3522–3533, Nov. 2015.

L. Shao, F. Zhu and X. Li, “Transfer Learning for Visual Categorization: A Survey”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 5, pp. 1019-1034, May 2015.

L. Liu, M. Yu and L. Shao, “Multiview Alignment Hashing for Efficient Image Search”, IEEE Transactions on Image Processing, vol. 24, no. 3, pp. 956-966, Mar. 2015.

K. Lu, N. He, J. Xue, J. Dong and L. Shao, “Learning View-Model Joint Relevance for 3D Object Retrieval”, IEEE Transactions on Image Processing, vol. 24, no. 5, pp. 1449 – 1459, May 2015.

Q. Zhu, L. Shao, X. Li and L. Wang, “Targeting Accurate Object Extraction From an Image: A Comprehensive Study of Natural Image Matting”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 2 pp. 185-207, Feb. 2015.

L. Liu, L. Shao and F. Zheng and X. Li, “Realistic Action Recognition via Sparsely-Constructed Gaussian Processes”, Pattern Recognition, vol. 47, no. 12, pp. 3819-3827, Dec. 2014.

J. Han, C. Chen, L. Shao, X. Hu, J. Han and T. Liu, “Learning Computational Models of Video Memorability from fMRI Brain Imaging”, IEEE Transactions on Cybernetics, vol. 45, no. 8, pp. 1692-1703, Aug. 2015.

X. Wen, L. Shao, W. Fang and Y. Xue, “Efficient Feature Selection and Classification for Vehicle Detection”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 25, no. 3, pp. 508-517, Mar. 2015.

L. Zhang, X. Zhen and L. Shao, “Learning Object-to-Class Kernels for Scene Classification”, IEEE Transactions on Image Processing, vol. 23, no. 8, pp. 3241-3253, Aug. 2014.

F. Zhu and L. Shao, Weakly-Supervised Cross-Domain Dictionary Learning for Visual Recognition”, International Journal of Computer Vision (IJCV), vol. 109, no. 1-2, pp. 42-59, Aug. 2014. [Code]

L. Shao, D. Wu and X. Li, Learning Deep and Wide: A Spectral Method for Learning Deep Networks”, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 12, pp. 2303-2308, Dec. 2014. [Top 1 Most Frequently Downloaded Paper of TNNLS in Dec. 2014]

L. Shao, R. Yan, X. Li and Y. Liu, “From Heuristic Optimization to Dictionary Learning: A Review and Comprehensive Comparison of Image Denoising Algorithms”, IEEE Transactions on Cybernetics, vol. 44, no. 7, pp. 1001-1013, Jul. 2014.

J. Tang, L. Shao and X. Li, “Efficient Dictionary Learning for Visual Categorization”, Computer Vision and Image Understanding, vol. 124, pp. 91-98, Jul. 2014.

L. Shao, L. Liu and X. Li, “Feature Learning for Image Classification via Multiobjective Genetic Programming”, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 7, pp. 1359-1371, Jul. 2014. [Impact Factor: 4.370]

J. Tang, L. Shao and X. Zhen, “Robust Point Pattern Matching Based on Spectral Context”, Pattern Recognition, vol. 47, no. 3, pp. 1469-1484, Mar. 2014.

R. Yan, L. Shao and Y. Liu, “Nonlocal Hierarchical Dictionary Learning Using Wavelets for Image Denoising”, IEEE Transactions on Image Processing, vol. 22, no. 12, pp. 4689-4698, Dec. 2013.

L. Shao, X. Zhen, D. Tao and X. Li, “Spatio-Temporal Laplacian Pyramid Coding for Action Recognition”, IEEE Transactions on Cybernetics, vol. 44, no. 6, pp. 817-827, Jun. 2014. [Code]

L. Shao, S. Jones and X. Li, “Efficient Search and Localization of Human Actions in Video Databases”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 24, no. 3, pp. 504-512, Mar. 2014.

L. Shao, J. Han, D. Xu and J. Shotton, “Computer Vision for RGB-D Sensors: Kinect and Its Applications”, IEEE Transactions on Cybernetics, vol. 43, no. 5, pp. 1313-1316, Oct. 2013.

J. Han, L. Shao, D. Xu and J. Shotton, “Enhanced Computer Vision with Microsoft Kinect Sensor: A Review”, IEEE Transactions on Cybernetics, vol. 43, no. 5, pp. 1317-1333, Oct. 2013. [Top 1 Most Frequently Downloaded Paper of T-CYB in 2013-2017]

S. Jones and L. Shao, “Content-Based Retrieval of Human Actions from Realistic Video Databases”, Information Sciences, vol. 236, pp. 56-65, Jul. 2013. [Impact Factor: 3.643]

L. Liu, L. Shao, X. Zhen and X. Li, “Learning Discriminative Key Poses for Action Recognition”, IEEE Transactions on Cybernetics, vol. 43, no. 6, pp. 1860-1870, Dec. 2013. (Previously Known as: IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics) [Impact Factor: 3.781]

X. Zhen, L. Shao, D. Tao and X. Li, “Embedding Motion and Structure Features for Human Action Recognition”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 7, pp. 1182-1190, Jul. 2013.

L. Liu, L. Shao and P. Rockett, “Boosted Key-Frame Selection and Correlated Pyramidal Motion-Feature Representation for Human Action Recognition”, Pattern Recognition, vol. 46, no. 7, pp. 1810-1818, Jul. 2013.

D. Wu and L. Shao, “Silhouette Analysis-Based Action Recognition Via Exploiting Human Poses”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 2, pp. 236-243, Feb. 2013.

L. Shao, L. Ji, Y. Liu and J. Zhang, “Human Action Segmentation and Recognition via Motion and Shape Analysis”, Pattern Recognition Letters, vol. 33, no. 4, pp. 438-445, Mar. 2012. [Most Downloaded Article of PRL in 2013]

L. Shao, H. Zhang and G. de Haan, “An Overview and Performance Evaluation of Classification Based Least Squares Trained Filters”, IEEE Transactions on Image Processing, vol. 17, no. 10, pp. 1772-1782, Oct. 2008.

L. Shao, T. Kadir and M. Brady, “Geometric and Photometric Invariant Distinctive Regions Detection”, Information Sciences, vol. 177, no. 4, pp. 1088-1122, Feb. 2007. [Impact Factor: 3.893]

L. Shao and M. Brady, “Specific Object Retrieval Based on Salient Regions”, Pattern Recognition, vol. 39, no. 10, pp. 1932-1948, Oct. 2006.

Conference Papers

J. Qin, L. Liu, L. Shao, B. Ni, C. Chen, F. Shen and Y. Wang, “Binary Coding for Partial Action Analysis with Limited Observation Ratios”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

L. Liu, L. Shao, F. Shen and M. Yu, “Discretely Coding Semantic Rank Orders for Supervised Image Hashing”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

Y. Long, L. Liu, L. Shao, F. Shen, G. Ding and J. Han, “From Zero-Shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

J. Qin, L. Liu, L. Shao, F. Shen, B. Ni, J. Chen and Y. Wang, “Zero-Shot Action Recognition with Error-Correcting Output Codes”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

L. Liu, F. Shen, Y. Shen, X. Liu and L. Shao, “Deep Sketch Hashing: Fast Free-Hand Sketch-Based Image Retrieval”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017. [Spotlight Paper]

J. Chen, Y. Wang, J. Qin, L. Liu and L. Shao, “Fast Person Re-Identification via Cross-Camera Semantic Binary Transformation”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

Y. Huang, L. Shao and A. Frangi, “Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images Using Weakly-Supervised Joint Convolutional Sparse Coding”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

L. Liu, Y. Zhou and L. Shao, “DAP3D-Net: Where, What and How Actions Occur in Videos?”, IEEE International Conference on Robotics and Automation (ICRA), Singapore, 2017.

Y. Shen, L. Zhang and L. Shao, “Semi-Supervised Vision-Language Mapping via Variational Learning”, IEEE International Conference on Robotics and Automation (ICRA), Singapore, 2017.

Y. Long and L. Shao, “Describing Unseen Classes by Exemplars: Zero-shot Learning Using Grouped Simile Ensemble”, IEEE Winter Conference on Applications of Computer Vision (WACV), Santa Rosa, USA, 2017. 

Y. Long, L. Liu and L. Shao, “Towards Fine-grained Open Zero-shot Learning: Inferring Unseen Visual Features from Attributes”, IEEE Winter Conference on Applications of Computer Vision (WACV), Santa Rosa, USA, 2017.

Y. Zhou, L. Liu, L. Shao and M. Mellor, “DAVE: A Unified Framework for Fast Vehicle Detection and Annotation”, European Conference on Computer Vision (ECCV), Amsterdam, The Netherlands, 2016. [Dataset]

Y. Long, L. Liu and L. Shao, “Attribute Embedding with Visual-Semantic Ambiguity Removal for Zero-shot Learning”, British Machine Vision Conference (BMVC), York, UK, 2016.

F. Zheng and L. Shao, “Learning Cross-view Binary Identities for Fast Person Re-identification”, International Joint Conference on Artificial Intelligence (IJCAI), New York, USA, July 2016.

Y. Huang, F. Zhu, L. Shao and A. Frangi, “Color Object Recognition via Cross-Domain Learning on RGB-D Images”, IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.

J. Zhang, L. Zhang, H. Shum and L. Shao, “Arbitrary View Action Recognition via Transfer Dictionary Learning on Synthetic Training Data”, IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.

L. Liu, M. Yu and L. Shao, “Projection Bank: From High-dimensional Data to Medium-length Binary Codes”, IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, Dec. 2015.

Z. Cai, L. Liu, M. Yu and L. Shao, “Latent Structure Preserving Hashing”, British Machine Vision Conference (BMVC), Swansea, UK, 2015. [Oral – Acceptance Rate: 7%]

L. Liu, M. Yu and L. Shao, “Local Feature Binary Coding for Approximate Nearest Neighbor Search”, British Machine Vision Conference (BMVC), Swansea, UK, 2015. [Oral – Acceptance Rate: 7%]

J. Qin, L. Liu, M. Yu, Y. Wang and L. Shao, “Fast Action Retrieval from Videos via Feature Disaggregation”, British Machine Vision Conference (BMVC), Swansea, UK, 2015. [Oral – Acceptance Rate: 7%]

F. Zhu, L. Shao and M. Yu, Cross-Modality Submodular Dictionary Learning for Information Retrieval, ACM International Conference on Information and Knowledge Management (CIKM), Shanghai, China, 2014. [Oral]

D. Wu and L. Shao, “Multimodal Dynamic Networks for Gesture Recognition”, ACM International Conference on Multimedia (MM), Orlando, USA, 2014.

F. Zheng, L. Shao, J. Brownjohn and V. Racic “Learn++ for Robust Object Tracking”, British Machine Vision Conference (BMVC), Nottingham, UK, 2014. [Oral – Acceptance Rate: 7.7%]

X. Zhen, L. Shao and F. Zheng, “Discriminative Embedding via Image-to-Class Distances”, British Machine Vision Conference (BMVC), Nottingham, UK, 2014. [Oral – Acceptance Rate: 7.7%]

F. Zhu, L. Shao and J. Tang, “Boosted Cross-Domain Categorization”, British Machine Vision Conference (BMVC), Nottingham, UK, 2014. [Oral – Acceptance Rate: 7.7%] 

Q. Zhu, J. Mai and L. Shao, “Single Image Dehazing Using Color Attenuation Prior”, British Machine Vision Conference (BMVC), Nottingham, UK, 2014.

S. Jones and L. Shao, “Unsupervised Spectral Dual Assignment Clustering of Human Actions in Context”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, USA, 2014. [Oral – Acceptance Rate: 5.75%] [Code]

S. Jones and L. Shao, “A Multigraph Representation for Improved Unsupervised/Semi-supervised Learning of Human Actions”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, USA, 2014. [Code]

F. Zhu, Z. Jiang and L. Shao, “Submodular Object Recognition”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, USA, 2014.

D. Wu and L. Shao, “Leveraging Hierarchical Parametric Networks for Skeletal Joints Based Action Segmentation and Recognition”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, USA, 2014.

S. Jones and L. Shao, “Linear Regression Motion Analysis for Unsupervised Temporal Segmentation of Human Actions”, IEEE Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs, USA, 2014.

J. Tang and L. Shao and S. Jones,Point Pattern Matching Based on Line Graph Spectral Context and Descriptor Embedding”, IEEE Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs, USA, 2014.

L. Liu, L. Shao and X. Li, “Building Holistic Descriptors for Scene Recognition: A Multi-objective Genetic Programming Approach”, ACM International Conference on Multimedia (MM), Barcelona, Spain, 2013. [Full Paper: Oral]

F. Zhu and L. Shao, “Enhancing Action Recognition by Cross-Domain Dictionary Learning”, British Machine Vision Conference (BMVC), Bristol, UK, 2013. [Oral – Acceptance Rate: 7%]

R. Yan and L. Shao, “Image Blur Classification and Parameter Identification Using Two-stage Deep Belief Networks”, British Machine Vision Conference (BMVC), Bristol, UK, 2013.

L. Liu and L. Shao, “Learning Discriminative Representations from RGB-D Video Data”, International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, 2013. [Dataset]

L. Liu and L. Shao, “Synthesis of Spatio-Temporal Descriptors for Dynamic Hand Gesture Recognition Using Genetic Programming”, IEEE International Conference on Automatic Face and Gesture Recognition (FG), Shanghai, China, 2013.

X. Zhen and L. Shao, “Spatio-Temporal Steerable Pyramid for Human Action Recognition”, IEEE International Conference on Automatic Face and Gesture Recognition (FG), Shanghai, China, 2013.

L. Liu, L. Shao and P. Rockett, “Genetic Programming-Evolved Spatio-Temporal Descriptor for Human Action Recognition”, British Machine Vision Conference (BMVC), Surrey, UK, 2012.

D. Wu, F. Zhu, L. Shao and H. Zhang, “One Shot Learning Gesture Recognition with Kinect Sensor”, ACM International Conference on Multimedia (MM), Nara, Japan, 2012.

L. Shao and X. Chen, “Histogram of Body Poses and Spectral Regression Discriminant Analysis for Human Action Categorization”, British Machine Vision Conference (BMVC), Aberystwyth, UK, August-September 2010.

L. Shao and R. Mattivi, “Feature Detector and Descriptor Evaluation in Human Action Recognition”, ACM International Conference on Image and Video Retrieval (CIVR), Xi’an, China, July 2010.